remote sensing uav/drone technology as a ......remote sensing uav/drone technology as a tool for...

REMOTE SENSING UAV/DRONE TECHNOLOGY AS A TOOL FOR URBAN

DEVELOPMENT MEASURES IN APCRDA

T. Preethi Latha1,*, K.NagaSundari1, Sreedhar Cherukuri I.A.S1, M.V.V.S.V.Prasad1

1Andhra Pradesh Capital Region Development Authority (APCRDA), Municipal Administration and Urban Development (MA&UD), Govt. of Andhra Pradesh, India – [email protected]*,

[email protected], [email protected], [email protected]

Commission VI, WG VI/4

KEY WORDS: Remote Sensing, UAV/Drone, Buildings occupancy, Urban Development, Planning, Smart Cities

ABSTRACT:

Now-a-days, collecting accurate and meaningful information about the urban localities/environment with the maximum efficiency in

terms of cost and time has become more relevant for urban, rural and city level development planning and administration. This work

presents a technical procedure for automatic extraction of building information and characterization of different urban building types

within the Andhra Pradesh Capital Region Development Authority (APCRDA) jurisdiction areas using UAVs. The methodology

consists of a number of sequential processes of acquisition and generation of high resolution Orthomosaic images, creation of 3D

point cloud data, and image classification algorithm for feature extraction using exclusively the geometric coordinates. The main

parameters of the urban structures/buildings assessed in this work are site area of the building, built-up area, and building

dimensions, building setbacks and building height. Different geometric and appropriate metrics were automatically extracted for

each of the elements, defining the urban typology. In this study, residential and commercial buildings were considered for the

analysis and the measurements from Drone were validated with respective approved plans and manual inspections and showed

positive results with threshold parameters like setbacks and height as per building bye-laws of Andhra Pradesh Government Order

(G.O) 119. Based on the results, measurements from Drone are used for the buildings occupancy permissions following the State

government building rules. This automated system would replace physical inspections and manual reports and significantly reduce

costs and improve efficiency. As an important component in this pilot study, visualisation of the building information were

represented / displayed on a web application in an interactive mode. This added value of UAV technology with an automated system

in comparison with traditional ways provides geospatial information and can also be considered as an essential Earth Observation

indicator which has the potential to lead to next generation Urban Information Services and in the Smart cities development. The

considerable potential use of these indicators in urban planning and development offers an opportunity in appropriate decision

making in day to day urban planning measures.

1. INTRODUCTION

1.1 Background

Urban decision making increasingly requires urban land-use and

land-cover maps generated from very high spatial resolution

data. Remote Sensing is well advanced in terms of technologies

and methods like multi-sensor, multi-scale and multi-temporal

analyses are primarily limited to roof top view of the buildings

which represents an incomplete perspective of understanding

the urban systems.

During the past 50 years, measurement technologies in

surveying and engineering has made significant developments

by introducing the surveying methods like Electronic Total

Station (ETS), GPS, Robotic total station and laser scanner.

In recent years, the Unmanned Aircraft systems/UAVs/Drones

have become the most advanced technology developed and a

perfect platform for aerial photography, remote sensing studies,

topographical surveys and mapping. These UAVs also make use

of LIDAR and data derived from these active sensors capable of

providing detailed 3D pint clouds from which detailed building

structural information can be defined for urban planning and

development measures. Many remote sensing and

photogrammetry software packages are available, led by Leica,

and drone data processing softwares like Drone Mapper,

Photomodeler, Pix4D, Drone2Map from ESRIs platform,

Agisoft Photoscan etc., can produce high resolution

orthomosaics,3D information in accuracy that is equal to or

better than conventional aerial photography. Standard GIS

softwares and AutoCAD can be used to stitch and georeference

drone aerial photos. Recent developments in Web based

technologies using GIS; the drone derived outputs can be

displayed by representing 2D and 3D information through

webportals/dashboards.

Various building detection techniques have been reported

during the last two decades like using algorithms in 2D and 3D

information from photogrammetric imagery, integration of

LIDAR and imagery for advance building detections, building

heights and boundaries using LIDAR data. Recent break

throughs in LIDAR (Hinks et. al., 2009) and UAV/Drone flight

path planning which emphasizes building façade/footprint data

capture, has greatly facilitated the potential for rapid auto-

generation of 3D building models. However, the automatic

building detection is still largely impeded by scene complexity,

incomplete cue extraction and sensor dependency of data (Sohn

and Dowman, 2007).Vegetation, and especially trees, can be the

prime cause of scene complexity and incomplete feature

extraction. Important building cues can be completely or

partially missed due to occlusions and shadowing from trees

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W13, 2019 ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands

This contribution has been peer-reviewed. https://doi.org/10.5194/isprs-archives-XLII-2-W13-525-2019 | © Authors 2019. CC BY 4.0 License.

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mailto:[email protected]*

mailto:[email protected]



(Awrangjeb et al., 2012). Goodwin et al., 2009 provided

convincing examples of the use of small foot print in extracting

building outlines and urban cover and structure information.

The present pilot study explains the technical methodology of

Drone survey to extract building information and automatic

report generation in the Andhra Pradesh Capital Region

Development Authority (APCRDA) jurisdiction using UAVs.

2. UAV / DRONE APPLICATION IN APCRDA

In APCRDA, Planning department has implemented Andhra

Pradesh Development Permission Management System

(APDPMS) one of the major online building permission

approval systems facilitating the automatic building permissions

for the entire capital region as shown in Figure 1(a). It facilitates

the integration of database from different departments like

revenue data, registration, property tax, municipal

properties/Govt. properties, Approved Layouts etc. As on today,

as per building bye-laws of Andhra Pradesh Government Order

(G.O) 119 a total of ~79 buildings were approved through the

online system for occupancy issuance among #93 with 4.3%

record of rejected buildings as shown in Figure 1(b).

Figure 1: (a) Andhra Pradesh Capital Region Development

Authority (APCRDA) jurisdiction (b) Statistics of Occupancy

Building permissions through APDPMS

Currently, the Building approvals for Occupancy are taking

place based on the traditional approach of site inspections using

traditional surveying methods by taking manual measurements

for the buildings. These traditional methods can be replaced by

implementing the latest technologies like UAV/ Drone Surveys,

from which the time & cost for site inspections can be

minimized from which accurate measurements can be obtained.

As a Pilot study, Drone survey method has been done in the

APCRDA jurisdiction for constructed buildings greater than

500Square meters of site area which were under occupancy

approval. Residential, Commercial, Public & Semi-public and

Industrial type of buildings were considered. The data acquired

from UAV / Drone surveys were analysed and able to extract

the building measurements like setbacks, dimensions/site area,

building heights etc.from the UAV data.Along with the building

measurements, Drone survey has also been done for

construction monitoring in the high density urban areas which

further helped in the identification of constructions made

without approvals in monthly intervals as shown in Figure 2.

Figure 2: Construction monitoring in the dense urban area using

drone survey at two time intervals.

3. STUDY AREA

The study sites were located randomly for the buildings under

occupancy issuance in the Andhra Pradesh Capital Region

Development Authority (APCRDA) jurisdiction which has been

subdivided into 9 Zonal areas. A total of 78 buildings were

surveyed using Drone technology as shown in the Figure 3(a).

Figure 3(b) represents the #2occupancy building sites

considered for the analysis and comparison study.

Figure 3: (a) Drone surveyed building locations (b) Buildings

selected for the analysis

4. METHODOLOGY

The workflow of the pilot study was done by using the

Unmanned Armed Vehicle DJI Phantom 4 pro to acquire all the

aerial images. The entire methodology has been described as

represented in the Figure 4.



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Figure 4: Flowchart representing automatic building

information generation using UAVs/Drone

4.1 UAVFlight Plan and Image Collection

In regard to the UAV specifications, it is equipped with a built

in camera and gimbal system.UAV carries a 1”CMOS sensor

which captures 20 effective megapixel images.The aircraft with

standard calibration method flies in a P-mode i.e., positioning

mode which works best when the GPS signal is strong. The

UAV utilizes GPS, stereo vision system and infrared sensing

system to stabilize, avoid obstacles or track moving objects. The

data collection by the UAV differs by the type of flight path.

The grid mission is the best suited one to generate 2D maps

from the images. The circular and double grid missions were

designed to create 3D models of objects like buildings etc. As

shown in Figure 5. Nadir view images (Figure 5(a)) were

mostly used for the creation of Digital Terrain (or Surface)

Models (Aicardi et al., 2016). As the information provided with

the nadir images will not be sufficient to successfully capture

the details of the building facades. That is why oblique images

(Figure 5(b)) were becoming more important in the UAV

photogrammetric process by capturing the images without any

overlap from end to end at a desired angle of 45o.

Figure 5: Data collection by using two flight plans (a) Double

grid mission/linear mission (b) Circular mission

4.2 Data Processing and Visualization

The UAV collected raw RGB images were inserted to the cloud

processing platform which uses photogrammetric image

processing algorithms with 90% overlapping, low altitude and

high resolution RGB imagery as an input, 3D point clouds,

orthomosaic and 3D digital surface models were created.

Traditional stereovision uses 2D images from multiple view

angles to construct a 3D model as shown in Figure 4.

Prior to generating the orthomosaic, a 3D point cloud is

generated. The main aim of process is to produce a

georeferenced 3D point cloud by handling with overlapping

aerial image data. The point cloud generated by using the

captured images and can also be edited to remove any spurious

points, which further used to view a 3D model, where all the

dots of the point cloud are connected in order to create a

surface. The mesh can contain artefacts, especially around the

edges of the project where there will have been less image

overlap. The mesh is useful to show the building sites looked

like and it can be rotated and viewed from any angle; however,

it should not be taken to be the visual truth and it is not a

substitute for analysing the underlying images that created it.

Figure 7: Building outputs generated after data processing(a)

Orthomosaic image (b) 3D Building model

Point cloud data plays a significant role in various geospatial

applications as it conveys plentiful information which can be

used for different types of analysis. In the present study, using

Potree (Potree, 2015), an open source WebGL point cloud

render, the customized 2D & 3D visualization portal named as

3rdi(Read as Third Eye) has been designed which supports level

of detail point cloud rendering generated using UAV with an

automatic report generation system.

Our experimental study demonstrated its performance by

displaying the building models on GIS base maps, interactively

manipulating large building point cloud data sets such as

rotating, scaling, extracting the building measurements of

setbacks, height, dimensions etc. as shown in Figure 8.

Figure 8: Visualization web portal of the 3D building model

A Set Back tool has been developed in the customized viewer

for setback measurements of the buildings (Figure 9) in order to

minimize the errors and increase the accuracy. The automatic

report generation has also been included in the visualization

portal.



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Figure 9: Setback measurement tool included in the 3D viewing

webportal.

4. EXPERIMENTAL RESULTS

In this study, two residential building with varying extents were

considered and the building measurements were taken as per the

methodology explained. The results obtained from the drone

imagery were compared with the approved/sanctioned plans as

shown in the Figures 10 and 11. The data in Table1 and Table 2

shows the positive differences from approved defined

measurements and drone derived measurements which are in

acceptable format as per the building rules and regulations of

G.O 119. This explains that the deviation difference in the

building setback measurements can be positive up to 10%

which are acceptable. The positive differences may vary to each

building type which again depends on the compound wall

thickness, plantations etc.

If the deviation difference goes below -10% i.e. the negative

deviations are not acceptable. These are limited to the cases like

architectural elevations, deviations in the plan to ground reality,

physical obstacles, under construction works etc.

The differences calculated from the drone imagery data

approved plans show reasonably promising results which

demonstrate the potential and implementation of UAV based

surveys in the urban development measures.

4.1 Building-1

Figure 10: Building 1 3D and foot print view derived from

Drone

Table 1: Building 1 measurements derived from Drone

4.2 Building-2

Figure 11: Building 2 3D and foot print view derived from

Drone

Table 2: Building 2 measurements derived from Drone

5. CONCLUSIONS

In this research we evaluated the use of a UAV platform for

urban applications and the experimental results demonstrated

it’s potential. This is the first of its kind pilot study that has

been taken up in the APCRDA jurisdiction for the urban e-

governance and smart city development applications.

Building

Parameters

Approved

Plan

Drone

Imagery Difference

Building Height 16 16.48 0.48

No. of Floors S+G+4 S+G+4 -

Built-up area 410.60 416.42 5.82

Building

Dimensions

North 12.39 12.42 0.03

East 33.14 33.53 0.39

West 33.14 33.54 0.40

South 12.39 12.42 0.03

Building

Setbacks

North 4.60,4.60 4.19,4.21 0.41,0.39

East 3,3 3.02,3.05 0.02,0.05

West 3.50,3.50 3.22,3.18 0.28,0.32

South 2.50,2.50 2.20,2.18 0.30,0.32

Building

Parameters

Approved

Plan

Drone

Imagery Difference

Building Height 15 15.38 0.38

No. of Floors S+G+4 S+G+4 -

Built-up area 1148.27 1155.95 7.65

Building

Dimensions

North 22.48 22.64 0.16

East 51.08 51.10 0.02

West 51.08 51.04 0.04

South 22.48 22.63 0.15

Building

Setbacks

North 5,5 5.36,5.20 0.36,0.2

East 5,5 4.84,4.94 0.5,0.06

West 3,3 3,3.05 0,0.05

South 5,2.50 4.93,4.96 0.07,2.46



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UAV as an alternative platform for 3D point cloud acquisition

offers potentials because of its flexibility and practicability

combined with low cost of implementations. Along with the

building feature detection techniques, the drones are very much

useful in identification of the unauthorized constructions,

building construction monitoring, and land developments. There

are some limitations that should be taken into account in the

UAV data processing. To fully implement the UAV platform as

a suitable tool for urban applications, technological advances in

RTK mode UAVs provide much higher accuracy of the UAVs

location and improvements of sensors will also increase the

spatial accuracy. With the current advancement in recent

technologies, utilization and implementation of UAVs in urban

planning and development also useful for smart city

development and provide an opportunity for appropriate

decision making in day to day urban planning measures.

ACKNOWLEDGEMENTS

Our sincere thanks to the XYZ Innovations Private Limited

team for the technical support to carry out the Drone survey.

REFERENCES

Aicardi, I., Chiabrando, F., Grasso, N., Lingua, A. M., Noardo,

F., Spano, A., 2016. UAV Photogrammetry with Oblique

Images: First Analysis on Data Acquisition and Processing.

ISPRS International Archives of the Photogrammetry, Remote

Sensing and Spatial Inf. Sci., XLI-B1, 835–42.

Andhra Pradesh Development Permission Management System,

Andhra Pradesh, India, 2016. http://apdpms.ap.gov.in

APGOMS No. 119 MAUD (M) Department: AP Buildings

rules dated 28.03.2017. https://goir.ap.gov.in.

Awrangjeb, M. and Fraser, C. S., 2012. An automatic and

threshold-free performance evaluation system for building

extraction techniques from airborne LIDAR data. IEEE Journal

of Selected Topics in Applied Earth Observations and Remote

Sensing, 7(10), 4184–4198.

Goodwin, N. R., Coops, N. C., Tooke, T. R., Christen, A.,

Voogt, J. A., 2009. Characterizing urban surface cover and

structure with airborne LiDAR technology. Canadian Journal

of Remote Sensing, 35(3), 297-309.

Hinks, T., Carr, H., Laefer, D. F., 2009. Flight optimization

algorithms for aerial LiDAR capture for urban infrastructure

model generation. Journal of Computing in Civil Engineering,

23(6), 330-9.

https://www.dji.com/phantom-4-pro/info#downloads

Potree, 2015. http://www.potree.org/.

Sohn, G. and Dowman, I., 2007. Data fusion of high-resolution

satellite imagery and LIDAR data for automatic building

extraction. ISPRS Journal.



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http://apdpms.ap.gov.in/

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